Class-specific diffractive cameras based on deep learning-designed surfaces

被引:0
|
作者
Xuxi Zhou
Shuming Wang
机构
[1] Nanjing University,National Laboratory of Solid
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Recently, a new diffractive camera design based on transmissive surfaces structured using deep learning is proposed. It performs class-specific imaging of target objects and all-optical deletion of other classes of objects, which will promote the development of privacy-preserving digital cameras and mission-specific data.
引用
收藏
相关论文
共 50 条
  • [1] Class-specific diffractive cameras based on deep learning-designed surfaces
    Zhou, Xuxi
    Wang, Shuming
    LIGHT-SCIENCE & APPLICATIONS, 2022, 11 (01)
  • [2] Deep Learning-designed Diffractive Neural Networks
    Lin, Xing
    Riverson, Yair
    Yardimci, Nezih T.
    Veli, Muhammed
    Luo, Yi
    Jarrahi, Mona
    Ozcan, Aydogan
    2019 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), 2019,
  • [3] To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects
    Bai, Bijie
    Luo, Yi
    Gan, Tianyi
    Hu, Jingtian
    Li, Yuhang
    Zhao, Yifan
    Mengu, Deniz
    Jarrahi, Mona
    Ozcan, Aydogan
    ELIGHT, 2022, 2 (01):
  • [4] To image, or not to image: class-specific diffractive cameras with all-optical erasure of undesired objects
    Bijie Bai
    Yi Luo
    Tianyi Gan
    Jingtian Hu
    Yuhang Li
    Yifan Zhao
    Deniz Mengu
    Mona Jarrahi
    Aydogan Ozcan
    eLight, 2
  • [5] Unidirectional imaging using deep learning-designed materials
    Li, Jingxi
    Gan, Tianyi
    Zhao, Yifan
    Bai, Bijie
    Shen, Che-Yung
    Sun, Songyu
    Jarrahi, Mona
    Ozcan, Aydogan
    SCIENCE ADVANCES, 2023, 9 (17)
  • [6] Deep reinforcement learning-designed radiofrequency waveform in MRI
    Shin, Dongmyung
    Kim, Younghoon
    Oh, Chungseok
    An, Hongjun
    Park, Juhyung
    Kim, Jiye
    Lee, Jongho
    NATURE MACHINE INTELLIGENCE, 2021, 3 (11) : 985 - 994
  • [7] Deep reinforcement learning-designed radiofrequency waveform in MRI
    Dongmyung Shin
    Younghoon Kim
    Chungseok Oh
    Hongjun An
    Juhyung Park
    Jiye Kim
    Jongho Lee
    Nature Machine Intelligence, 2021, 3 : 985 - 994
  • [8] Learning discrete class-specific prototypes for deep semantic hashing
    Ma, Lei
    Li, Xuan
    Shi, Yu
    Huang, Likun
    Huang, Zhenghua
    Wu, Jinmeng
    NEUROCOMPUTING, 2021, 443 : 85 - 95
  • [9] Universal Polarization Transformations: Spatial Programming of Polarization Scattering Matrices Using a Deep Learning-Designed Diffractive Polarization Transformer
    Li, Yuhang
    Li, Jingxi
    Zhao, Yifan
    Gan, Tianyi
    Hu, Jingtian
    Jarrahi, Mona
    Ozcan, Aydogan
    ADVANCED MATERIALS, 2023, 35 (51)
  • [10] CLASS-SPECIFIC NONLINEAR SUBSPACE LEARNING BASED ON OPTIMIZED CLASS REPRESENTATION
    Iosifidis, Alexandros
    Tefas, Anastasios
    Pitas, Ioannis
    2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, : 2491 - 2495